Jan. 6, 2022, 2:10 a.m. | Francisco Villaescusa-Navarro, Shy Genel, Daniel Anglés-Alcázar, Lucia A. Perez, Pablo Villanueva-Domingo, Digvijay Wadekar, Helen Shao, Fai

cs.LG updates on arXiv.org arxiv.org

The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS)
project was developed to combine cosmology with astrophysics through thousands
of cosmological hydrodynamic simulations and machine learning. CAMELS contains
4,233 cosmological simulations, 2,049 N-body and 2,184 state-of-the-art
hydrodynamic simulations that sample a vast volume in parameter space. In this
paper we present the CAMELS public data release, describing the characteristics
of the CAMELS simulations and a variety of data products generated from them,
including halo, subhalo, galaxy, and void catalogues, power …

arxiv data project public public data

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